Overview

Brought to you by YData

Dataset statistics

Number of variables11
Number of observations52793
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory9.6 MiB
Average record size in memory190.7 B

Variable types

Numeric8
Text1
DateTime1
Boolean1

Alerts

attacks is highly overall correlated with scoreHigh correlation
days_since_first_war is highly overall correlated with war_idHigh correlation
faction_id is highly overall correlated with member_levelHigh correlation
member_id is highly overall correlated with member_levelHigh correlation
member_level is highly overall correlated with faction_id and 1 other fieldsHigh correlation
score is highly overall correlated with attacksHigh correlation
war_id is highly overall correlated with days_since_first_warHigh correlation
attacks has 20094 (38.1%) zeros Zeros
score has 20094 (38.1%) zeros Zeros

Reproduction

Analysis started2025-07-22 17:11:08.311805
Analysis finished2025-07-22 17:11:17.628428
Duration9.32 seconds
Software versionydata-profiling v0.0.dev0
Download configurationconfig.json

Variables

war_id
Real number (ℝ)

High correlation 

Distinct696
Distinct (%)1.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean23183.665
Minimum18131
Maximum28089
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size412.6 KiB
2025-07-22T12:11:17.735315image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Quantile statistics

Minimum18131
5-th percentile18680
Q120811
median23188
Q325710
95-th percentile27612
Maximum28089
Range9958
Interquartile range (IQR)4899

Descriptive statistics

Standard deviation2884.1246
Coefficient of variation (CV)0.12440331
Kurtosis-1.2242648
Mean23183.665
Median Absolute Deviation (MAD)2404
Skewness-0.026840762
Sum1.2239352 × 109
Variance8318174.6
MonotonicityNot monotonic
2025-07-22T12:11:18.010357image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
27742 200
 
0.4%
23798 200
 
0.4%
19304 200
 
0.4%
25852 200
 
0.4%
27455 199
 
0.4%
19557 199
 
0.4%
27141 199
 
0.4%
20811 199
 
0.4%
24583 198
 
0.4%
18680 198
 
0.4%
Other values (686) 50801
96.2%
ValueCountFrequency (%)
18131 25
 
< 0.1%
18134 40
 
0.1%
18155 24
 
< 0.1%
18178 190
0.4%
18189 47
 
0.1%
18214 27
 
0.1%
18215 30
 
0.1%
18242 195
0.4%
18247 170
0.3%
18248 31
 
0.1%
ValueCountFrequency (%)
28089 47
 
0.1%
28084 34
 
0.1%
28068 34
 
0.1%
28058 36
 
0.1%
28052 113
0.2%
28051 26
 
< 0.1%
28015 197
0.4%
28013 197
0.4%
28006 27
 
0.1%
27981 59
 
0.1%

faction_id
Real number (ℝ)

High correlation 

Distinct822
Distinct (%)1.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean29746.143
Minimum89
Maximum54339
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size412.6 KiB
2025-07-22T12:11:18.143417image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Quantile statistics

Minimum89
5-th percentile7002
Q111428
median29865
Q348640
95-th percentile52775
Maximum54339
Range54250
Interquartile range (IQR)37212

Descriptive statistics

Standard deviation17754.54
Coefficient of variation (CV)0.59686864
Kurtosis-1.5907719
Mean29746.143
Median Absolute Deviation (MAD)18596
Skewness-0.043645567
Sum1.5703881 × 109
Variance3.152237 × 108
MonotonicityNot monotonic
2025-07-22T12:11:18.277786image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
937 691
 
1.3%
21368 594
 
1.1%
7835 552
 
1.0%
23952 456
 
0.9%
14821 431
 
0.8%
8422 394
 
0.7%
8706 391
 
0.7%
21665 387
 
0.7%
8537 383
 
0.7%
8085 382
 
0.7%
Other values (812) 48132
91.2%
ValueCountFrequency (%)
89 100
 
0.2%
230 75
 
0.1%
231 275
 
0.5%
366 296
0.6%
478 84
 
0.2%
525 93
 
0.2%
937 691
1.3%
1117 52
 
0.1%
1251 18
 
< 0.1%
2095 57
 
0.1%
ValueCountFrequency (%)
54339 15
< 0.1%
54260 14
< 0.1%
54250 19
< 0.1%
54249 10
 
< 0.1%
54245 15
< 0.1%
54226 12
< 0.1%
54214 28
0.1%
54212 14
< 0.1%
54200 15
< 0.1%
54197 12
< 0.1%

member_id
Real number (ℝ)

High correlation 

Distinct31556
Distinct (%)59.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2606864
Minimum5
Maximum3869385
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size412.6 KiB
2025-07-22T12:11:18.441407image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Quantile statistics

Minimum5
5-th percentile521780.2
Q12160927
median2794601
Q33304693
95-th percentile3646737
Maximum3869385
Range3869380
Interquartile range (IQR)1143766

Descriptive statistics

Standard deviation895811.03
Coefficient of variation (CV)0.3436355
Kurtosis0.62039519
Mean2606864
Median Absolute Deviation (MAD)562610
Skewness-1.0772077
Sum1.3762417 × 1011
Variance8.0247739 × 1011
MonotonicityNot monotonic
2025-07-22T12:11:18.607482image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
2663371 7
 
< 0.1%
2928469 7
 
< 0.1%
1673083 7
 
< 0.1%
2520389 7
 
< 0.1%
225661 7
 
< 0.1%
1688185 7
 
< 0.1%
137261 7
 
< 0.1%
1288184 7
 
< 0.1%
2415291 7
 
< 0.1%
2361923 7
 
< 0.1%
Other values (31546) 52723
99.9%
ValueCountFrequency (%)
5 2
< 0.1%
37 3
< 0.1%
56 2
< 0.1%
89 3
< 0.1%
96 1
 
< 0.1%
145 2
< 0.1%
193 1
 
< 0.1%
262 1
 
< 0.1%
286 4
< 0.1%
567 1
 
< 0.1%
ValueCountFrequency (%)
3869385 1
< 0.1%
3867474 1
< 0.1%
3865415 1
< 0.1%
3861425 1
< 0.1%
3860687 1
< 0.1%
3856144 1
< 0.1%
3855794 1
< 0.1%
3853267 1
< 0.1%
3853136 1
< 0.1%
3852331 1
< 0.1%
Distinct31558
Distinct (%)59.8%
Missing0
Missing (%)0.0%
Memory size2.9 MiB
2025-07-22T12:11:19.051605image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length15
Median length11
Mean length8.6578713
Min length3

Characters and Unicode

Total characters457075
Distinct characters64
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique18715 ?
Unique (%)35.4%

Sample

1st rowValascaS
2nd rowTom--
3rd rowSchnitzel
4th rowVolny
5th rowTravis-
ValueCountFrequency (%)
pendragon 10
 
< 0.1%
lsd 10
 
< 0.1%
john 9
 
< 0.1%
deadpool 8
 
< 0.1%
johnny000 7
 
< 0.1%
breez 7
 
< 0.1%
vilmis 7
 
< 0.1%
neimles 7
 
< 0.1%
ledoksnis 7
 
< 0.1%
vecs 7
 
< 0.1%
Other values (31437) 52714
99.9%
2025-07-22T12:11:19.594118image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
e 37428
 
8.2%
a 36670
 
8.0%
i 27106
 
5.9%
o 27002
 
5.9%
r 25919
 
5.7%
n 23993
 
5.2%
l 18396
 
4.0%
t 17282
 
3.8%
s 16827
 
3.7%
u 11936
 
2.6%
Other values (54) 214516
46.9%

Most occurring categories

ValueCountFrequency (%)
(unknown) 457075
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
e 37428
 
8.2%
a 36670
 
8.0%
i 27106
 
5.9%
o 27002
 
5.9%
r 25919
 
5.7%
n 23993
 
5.2%
l 18396
 
4.0%
t 17282
 
3.8%
s 16827
 
3.7%
u 11936
 
2.6%
Other values (54) 214516
46.9%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 457075
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
e 37428
 
8.2%
a 36670
 
8.0%
i 27106
 
5.9%
o 27002
 
5.9%
r 25919
 
5.7%
n 23993
 
5.2%
l 18396
 
4.0%
t 17282
 
3.8%
s 16827
 
3.7%
u 11936
 
2.6%
Other values (54) 214516
46.9%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 457075
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
e 37428
 
8.2%
a 36670
 
8.0%
i 27106
 
5.9%
o 27002
 
5.9%
r 25919
 
5.7%
n 23993
 
5.2%
l 18396
 
4.0%
t 17282
 
3.8%
s 16827
 
3.7%
u 11936
 
2.6%
Other values (54) 214516
46.9%

member_level
Real number (ℝ)

High correlation 

Distinct100
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean57.191237
Minimum1
Maximum100
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size412.6 KiB
2025-07-22T12:11:19.735186image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile15
Q130
median52
Q390
95-th percentile100
Maximum100
Range99
Interquartile range (IQR)60

Descriptive statistics

Standard deviation30.809628
Coefficient of variation (CV)0.53871238
Kurtosis-1.4125145
Mean57.191237
Median Absolute Deviation (MAD)28
Skewness0.090472782
Sum3019297
Variance949.23317
MonotonicityNot monotonic
2025-07-22T12:11:19.862130image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
100 8377
 
15.9%
50 1470
 
2.8%
20 1234
 
2.3%
40 1226
 
2.3%
30 1106
 
2.1%
15 1059
 
2.0%
25 1047
 
2.0%
35 971
 
1.8%
99 944
 
1.8%
60 877
 
1.7%
Other values (90) 34482
65.3%
ValueCountFrequency (%)
1 85
 
0.2%
2 46
 
0.1%
3 146
0.3%
4 136
0.3%
5 144
0.3%
6 174
0.3%
7 174
0.3%
8 174
0.3%
9 257
0.5%
10 277
0.5%
ValueCountFrequency (%)
100 8377
15.9%
99 944
 
1.8%
98 374
 
0.7%
97 351
 
0.7%
96 418
 
0.8%
95 531
 
1.0%
94 388
 
0.7%
93 409
 
0.8%
92 438
 
0.8%
91 412
 
0.8%
Distinct541
Distinct (%)1.0%
Missing0
Missing (%)0.0%
Memory size412.6 KiB
Minimum2024-09-27 02:00:00
Maximum2025-07-19 18:00:00
Invalid dates0
Invalid dates (%)0.0%
2025-07-22T12:11:20.006406image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
2025-07-22T12:11:20.190727image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

war_duration_hours
Real number (ℝ)

Distinct548
Distinct (%)1.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean51.271756
Minimum3.13
Maximum116.02
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size412.6 KiB
2025-07-22T12:11:20.423834image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Quantile statistics

Minimum3.13
5-th percentile7.64
Q122.67
median48.36
Q380.02
95-th percentile104.02
Maximum116.02
Range112.89
Interquartile range (IQR)57.35

Descriptive statistics

Standard deviation31.937866
Coefficient of variation (CV)0.62291345
Kurtosis-1.1698968
Mean51.271756
Median Absolute Deviation (MAD)27.66
Skewness0.26423067
Sum2706789.8
Variance1020.0273
MonotonicityNot monotonic
2025-07-22T12:11:20.616860image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
95.02 855
 
1.6%
78.02 726
 
1.4%
91.02 697
 
1.3%
82.02 687
 
1.3%
100.02 574
 
1.1%
74.02 550
 
1.0%
58.02 514
 
1.0%
57.02 509
 
1.0%
101.02 505
 
1.0%
83.02 480
 
0.9%
Other values (538) 46696
88.5%
ValueCountFrequency (%)
3.13 196
0.4%
4.33 179
0.3%
4.4 117
 
0.2%
4.71 174
0.3%
4.78 200
0.4%
4.82 176
0.3%
5.11 179
0.3%
6.02 97
 
0.2%
6.34 174
0.3%
6.52 399
0.8%
ValueCountFrequency (%)
116.02 199
0.4%
115.61 34
 
0.1%
115.02 195
0.4%
113.02 192
0.4%
111.1 28
 
0.1%
111.02 163
0.3%
110.55 31
 
0.1%
110.02 28
 
0.1%
109.02 123
0.2%
108.13 40
 
0.1%

attacks
Real number (ℝ)

High correlation  Zeros 

Distinct247
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean16.770898
Minimum0
Maximum408
Zeros20094
Zeros (%)38.1%
Negative0
Negative (%)0.0%
Memory size412.6 KiB
2025-07-22T12:11:20.827756image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median4
Q321
95-th percentile74
Maximum408
Range408
Interquartile range (IQR)21

Descriptive statistics

Standard deviation28.309344
Coefficient of variation (CV)1.6880041
Kurtosis12.833922
Mean16.770898
Median Absolute Deviation (MAD)4
Skewness2.9801185
Sum885386
Variance801.41897
MonotonicityNot monotonic
2025-07-22T12:11:21.013849image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 20094
38.1%
1 2211
 
4.2%
2 1491
 
2.8%
4 1368
 
2.6%
5 1304
 
2.5%
3 1298
 
2.5%
10 1241
 
2.4%
6 1142
 
2.2%
7 959
 
1.8%
8 952
 
1.8%
Other values (237) 20733
39.3%
ValueCountFrequency (%)
0 20094
38.1%
1 2211
 
4.2%
2 1491
 
2.8%
3 1298
 
2.5%
4 1368
 
2.6%
5 1304
 
2.5%
6 1142
 
2.2%
7 959
 
1.8%
8 952
 
1.8%
9 873
 
1.7%
ValueCountFrequency (%)
408 1
< 0.1%
389 1
< 0.1%
354 1
< 0.1%
319 1
< 0.1%
308 1
< 0.1%
299 1
< 0.1%
281 1
< 0.1%
276 1
< 0.1%
274 2
< 0.1%
271 1
< 0.1%

score
Real number (ℝ)

High correlation  Zeros 

Distinct21774
Distinct (%)41.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean124.63114
Minimum0
Maximum10501.69
Zeros20094
Zeros (%)38.1%
Negative0
Negative (%)0.0%
Memory size412.6 KiB
2025-07-22T12:11:21.190339image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median28.32
Q3151.83
95-th percentile550.24
Maximum10501.69
Range10501.69
Interquartile range (IQR)151.83

Descriptive statistics

Standard deviation234.06994
Coefficient of variation (CV)1.8781017
Kurtosis101.09505
Mean124.63114
Median Absolute Deviation (MAD)28.32
Skewness5.540738
Sum6579651.6
Variance54788.739
MonotonicityNot monotonic
2025-07-22T12:11:21.354145image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 20094
38.1%
6.42 27
 
0.1%
6.6 24
 
< 0.1%
6.48 24
 
< 0.1%
6.24 19
 
< 0.1%
6.54 19
 
< 0.1%
10 17
 
< 0.1%
6.3 17
 
< 0.1%
6.18 16
 
< 0.1%
6.36 15
 
< 0.1%
Other values (21764) 32521
61.6%
ValueCountFrequency (%)
0 20094
38.1%
1.92 1
 
< 0.1%
2.06 4
 
< 0.1%
2.08 3
 
< 0.1%
2.1 2
 
< 0.1%
2.12 3
 
< 0.1%
2.13 1
 
< 0.1%
2.14 2
 
< 0.1%
2.16 1
 
< 0.1%
2.18 3
 
< 0.1%
ValueCountFrequency (%)
10501.69 1
< 0.1%
5012.31 1
< 0.1%
3856.93 1
< 0.1%
3663.08 1
< 0.1%
3638.85 1
< 0.1%
3557.97 1
< 0.1%
3551.33 1
< 0.1%
3442.22 1
< 0.1%
3411.96 1
< 0.1%
3292.45 1
< 0.1%
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size51.7 KiB
True
32699 
False
20094 
ValueCountFrequency (%)
True 32699
61.9%
False 20094
38.1%
2025-07-22T12:11:21.479915image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

days_since_first_war
Real number (ℝ)

High correlation 

Distinct131
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean162.38691
Minimum0
Maximum295
Zeros89
Zeros (%)0.2%
Negative0
Negative (%)0.0%
Memory size412.6 KiB
2025-07-22T12:11:21.605917image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile20
Q1105
median168
Q3237
95-th percentile280
Maximum295
Range295
Interquartile range (IQR)132

Descriptive statistics

Standard deviation82.229034
Coefficient of variation (CV)0.50637724
Kurtosis-1.1006928
Mean162.38691
Median Absolute Deviation (MAD)64
Skewness-0.22322969
Sum8572892
Variance6761.614
MonotonicityNot monotonic
2025-07-22T12:11:21.851161image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
106 1678
 
3.2%
50 1587
 
3.0%
239 1285
 
2.4%
230 1114
 
2.1%
260 1046
 
2.0%
160 916
 
1.7%
195 891
 
1.7%
113 874
 
1.7%
105 869
 
1.6%
43 856
 
1.6%
Other values (121) 41677
78.9%
ValueCountFrequency (%)
0 89
 
0.2%
6 434
0.8%
7 466
0.9%
8 692
1.3%
12 29
 
0.1%
13 298
0.6%
14 50
 
0.1%
15 399
0.8%
20 433
0.8%
21 346
0.7%
ValueCountFrequency (%)
295 160
 
0.3%
294 94
 
0.2%
293 36
 
0.1%
288 450
0.9%
287 608
1.2%
286 607
1.1%
281 374
0.7%
280 844
1.6%
279 157
 
0.3%
274 604
1.1%

Interactions

2025-07-22T12:11:16.219266image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
2025-07-22T12:11:09.056237image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
2025-07-22T12:11:10.189330image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
2025-07-22T12:11:11.230197image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
2025-07-22T12:11:12.350201image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
2025-07-22T12:11:13.223490image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
2025-07-22T12:11:14.165645image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
2025-07-22T12:11:15.183631image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
2025-07-22T12:11:16.348138image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
2025-07-22T12:11:09.164759image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
2025-07-22T12:11:10.316911image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
2025-07-22T12:11:11.379734image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
2025-07-22T12:11:12.462248image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
2025-07-22T12:11:13.344609image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
2025-07-22T12:11:14.284050image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
2025-07-22T12:11:15.284482image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
2025-07-22T12:11:16.470470image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
2025-07-22T12:11:09.356363image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
2025-07-22T12:11:10.438696image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
2025-07-22T12:11:11.525991image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
2025-07-22T12:11:12.585169image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
2025-07-22T12:11:13.449846image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
2025-07-22T12:11:14.395876image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
2025-07-22T12:11:15.395596image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
2025-07-22T12:11:16.597930image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
2025-07-22T12:11:09.500155image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
2025-07-22T12:11:10.587714image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
2025-07-22T12:11:11.663823image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
2025-07-22T12:11:12.695976image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
2025-07-22T12:11:13.559924image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
2025-07-22T12:11:14.527681image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
2025-07-22T12:11:15.520250image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
2025-07-22T12:11:16.705149image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
2025-07-22T12:11:09.622691image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
2025-07-22T12:11:10.701267image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
2025-07-22T12:11:11.787188image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
2025-07-22T12:11:12.802517image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
2025-07-22T12:11:13.660336image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
2025-07-22T12:11:14.641795image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
2025-07-22T12:11:15.641940image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
2025-07-22T12:11:16.824246image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
2025-07-22T12:11:09.758222image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
2025-07-22T12:11:10.850329image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
2025-07-22T12:11:11.955092image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
2025-07-22T12:11:12.909143image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
2025-07-22T12:11:13.761537image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
2025-07-22T12:11:14.787158image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
2025-07-22T12:11:15.765931image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
2025-07-22T12:11:16.944496image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
2025-07-22T12:11:09.900751image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
2025-07-22T12:11:10.979855image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
2025-07-22T12:11:12.104629image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
2025-07-22T12:11:13.014722image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
2025-07-22T12:11:13.860224image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
2025-07-22T12:11:14.896757image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
2025-07-22T12:11:15.919409image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
2025-07-22T12:11:17.076835image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
2025-07-22T12:11:10.041802image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
2025-07-22T12:11:11.104122image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
2025-07-22T12:11:12.225352image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
2025-07-22T12:11:13.113083image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
2025-07-22T12:11:14.067568image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
2025-07-22T12:11:15.036228image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
2025-07-22T12:11:16.060039image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Correlations

2025-07-22T12:11:21.957679image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
attacksdays_since_first_warfaction_idmember_idmember_levelparticipatedscorewar_duration_hourswar_id
attacks1.000-0.0250.079-0.0980.2100.3150.983-0.026-0.026
days_since_first_war-0.0251.0000.0440.098-0.0460.041-0.0260.0820.999
faction_id0.0790.0441.0000.476-0.5520.0810.019-0.0360.040
member_id-0.0980.0980.4761.000-0.7410.129-0.136-0.0650.093
member_level0.210-0.046-0.552-0.7411.0000.2590.2680.079-0.041
participated0.3150.0410.0810.1290.2591.0000.0790.1320.046
score0.983-0.0260.019-0.1360.2680.0791.000-0.030-0.027
war_duration_hours-0.0260.082-0.036-0.0650.0790.132-0.0301.0000.096
war_id-0.0260.9990.0400.093-0.0410.046-0.0270.0961.000

Missing values

2025-07-22T12:11:17.229760image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
A simple visualization of nullity by column.
2025-07-22T12:11:17.449291image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
Nullity matrix is a data-dense display which lets you quickly visually pick out patterns in data completion.

Sample

war_idfaction_idmember_idmember_namemember_levelwar_start_timewar_duration_hoursattacksscoreparticipateddays_since_first_war
028013332413498240ValascaS352025-07-11 14:00:0084.0215299.17True287
128013332413487587Tom--462025-07-11 14:00:0084.0217236.97True287
228013332411880691Schnitzel1002025-07-11 14:00:0084.0216218.82True287
328013332412890346Volny812025-07-11 14:00:0084.0220214.11True287
428013332411717276Travis-982025-07-11 14:00:0084.0217189.54True287
528013332412479416Slaterz1002025-07-11 14:00:0084.0216187.92True287
628013332412535063VanHorn992025-07-11 14:00:0084.0217175.26True287
728013332412002288kwartz1002025-07-11 14:00:0084.0215163.43True287
828013332412597200IndyCision692025-07-11 14:00:0084.0219157.75True287
928013332412116723Argozdoc1002025-07-11 14:00:0084.0213141.69True287
war_idfaction_idmember_idmember_namemember_levelwar_start_timewar_duration_hoursattacksscoreparticipateddays_since_first_war
5278320149524843050247Giellie302024-12-14 18:00:0076.1900.0False78
5278420149524843418287Coffee_Frog432024-12-14 18:00:0076.1900.0False78
5278520149524843427786NOTAC0P172024-12-14 18:00:0076.1900.0False78
5278620149524843506203BigPappaT212024-12-14 18:00:0076.1900.0False78
5278720149524843506777BIGSHOW1252024-12-14 18:00:0076.1900.0False78
5278820149524843512959BigMoney10112024-12-14 18:00:0076.1900.0False78
5278920149524843439230bubbaharris82024-12-14 18:00:0076.1900.0False78
5279020149524843498488BCdagoat202024-12-14 18:00:0076.1900.0False78
5279120149524843462764devious_nige452024-12-14 18:00:0076.1900.0False78
5279220149524843348344MamaDrgn432024-12-14 18:00:0076.1900.0False78